1. Technical Field
The present invention relates to digital pathology and, more particularly, to image analysis performed with whole-slide imaging.
2. Description of the Related Art
Pathologists and medical doctors analyze very large digital images of whole histopathology slides using whole-slide imaging browsers. Such browsers form a kind of virtual microscope running on a computer, allowing a user to manipulate the image in a user-friendly fashion, e.g., by panning and zooming, and implement computer-based image analysis on the slide. Image analysis normally operates on a portion of the image, called the region of interest (ROI), but the size of the ROI is often constrained by the complexity of the analysis and the available computing resources. Analytics on histopathological images, including image processing, image analysis, and machine learning, is frequently computationally intensive and cannot be performed in an interactive way.
Existing systems are desktop or web-browser based and perform viewing and limited analysis. These systems do not have the capability of executing full analysis of tissues. As a result, analysis on such systems is not scalable, and demanding functions take too long for interactive execution.
Furthermore, existing distributed computing systems are inadequate to address the needs of digital pathology, because the computation and communication demands may overwhelm even powerful distributed systems. Images of histology slides can be, for example, several gigabytes in size, such that it is usually infeasible to transfer such images back and forth between client and server. Moreover, the computations involved in modern analytics can be very intensive, particularly if performed on the entire image. As such, existing cloud servers are not optimized to handle digital pathology services.